Indoor Navigation and Location-Based Services for Persons with Motor Limitations

Riga, Paraskevi

doi:10.4018/978-1-4666-4442-7.ch006

Cited by 1 publication

(2 citation statements)

References 48 publications

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“…The problem in GPS is mainly being a line of sight based technology working in outdoor environment only. GPS signals are not available in indoor scenarios so for this purpose indoor localization or object tracking technologies are used [2,3].…”

Section: Introductionmentioning

confidence: 99%

“…Other than this, in case of industrial application or automation finding, the location of an object needs accurate solutions. The reason for this difference in accuracy depends on indoor environment such as physical objects, presence of humans, radio signals, temperature which creates interference in the received signals and hence variations in the received signals occurs [3,4].…”

Section: Introductionmentioning

confidence: 99%

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Hybrid Indoor Position Estimation using K-NN and MinMax

Subhan¹,

Ahmed²,

Haider³

et al. 2019

KSII TIIS

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Due to the rapid advancement in smart phones, numerous new specifications are developed for variety of applications ranging from health monitoring to navigations and tracking. The word indoor navigation means location identification, however, where GPS signals are not available, accurate indoor localization is a challenging task due to variation in the received signals which directly affect distance estimation process. This paper proposes a hybrid approach which integrates fingerprinting based K-Nearest Neighbors (K-NN) and lateration based MinMax position estimation technique. The novel idea behind this hybrid approach is to use Euclidian distance formulation for distance estimates instead of indoor radio channel modeling which is used to convert the received signal to distance estimates. Due to unpredictable behavior of the received signal, modeling indoor environment for distance estimates is a challenging task which ultimately results in distance estimation error and hence affects position estimation process. Our proposed idea is indoor position estimation technique using Bluetooth enabled smart phones which is independent of the radio channels. Experimental results conclude that, our proposed hybrid approach performs better in terms of mean error compared to Trilateration, MinMax, K-NN, and existing Hybrid approach.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%